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Design AWS architectures for startups using serverless patterns and IaC templates. Use when asked to design serverless architecture, create CloudFormation templates, optimize AWS costs, set up CI/CD pipelines, or migrate to AWS. Covers Lambda, API Gateway, DynamoDB, ECS, Aurora,
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Design AWS architectures for startups using serverless patterns and IaC templates. Use when asked to design serverless architecture, create CloudFormation templates, optimize AWS costs, set up CI/CD pipelines, or migrate to AWS. Covers Lambda, API Gateway, DynamoDB, ECS, Aurora, 📦 Ships with claude-skills
</> SKILL.md
aws-solution-architect.SKILL.md
---
name : "aws-solution-architect"
description : Design AWS architectures for startups using serverless patterns and IaC templates. Use when asked to design serverless architecture, create CloudFormation templates, optimize AWS costs, set up CI/CD pipelines, or migrate to AWS. Covers Lambda, API Gateway, DynamoDB, ECS, Aurora, and cost optimization.
---
# AWS Solution Architect
Design scalable, cost-effective AWS architectures for startups with infrastructure-as-code templates.
---
## Workflow
### Step 1: Gather Requirements
Collect application specifications:
```
- Application type (web app, mobile backend, data pipeline, SaaS)
- Expected users and requests per second
- Budget constraints (monthly spend limit)
- Team size and AWS experience level
- Compliance requirements (GDPR, HIPAA, SOC 2)
- Availability requirements (SLA, RPO/RTO)
```
### Step 2: Design Architecture
Run the architecture designer to get pattern recommendations:
```bash
python scripts/architecture_designer.py --input requirements.json
```
**Example output:**
```json
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{
"recommended_pattern": "serverless_web",
"service_stack": ["S3", "CloudFront", "API Gateway", "Lambda", "DynamoDB", "Cognito"],
"estimated_monthly_cost_usd": 35,
"pros": ["Low ops overhead", "Pay-per-use", "Auto-scaling"],
"cons": ["Cold starts", "15-min Lambda limit", "Eventual consistency"]
}
```
Select from recommended patterns:
- **Serverless Web**: S3 + CloudFront + API Gateway + Lambda + DynamoDB
- **Event-Driven Microservices**: EventBridge + Lambda + SQS + Step Functions
- **Three-Tier**: ALB + ECS Fargate + Aurora + ElastiCache
- **GraphQL Backend**: AppSync + Lambda + DynamoDB + Cognito
See `references/architecture_patterns.md` for detailed pattern specifications.
**Validation checkpoint:** Confirm the recommended pattern matches the team's operational maturity and compliance requirements before proceeding to Step 3.
### Step 3: Generate IaC Templates
Create infrastructure-as-code for the selected pattern:
```bash
# Serverless stack (CloudFormation)
python scripts/serverless_stack.py --app-name my-app --region us-east-1
```
**Example CloudFormation YAML output (core serverless resources):**
```yaml
AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31
Parameters:
AppName:
Type: String
Default: my-app
Resources:
ApiFunction:
Type: AWS::Serverless::Function
Properties:
Handler: index.handler
Runtime: nodejs20.x
MemorySize: 512
Timeout: 30
Environment:
Variables:
TABLE_NAME: !Ref DataTable
Policies:
- DynamoDBCrudPolicy:
TableName: !Ref DataTable
Events:
ApiEvent:
Type: Api
Properties:
Path: /{proxy+}
Method: ANY
DataTable:
Type: AWS::DynamoDB::Table
Properties:
BillingMode: PAY_PER_REQUEST
AttributeDefinitions:
- AttributeName: pk
AttributeType: S
- AttributeName: sk
AttributeType: S
KeySchema:
- AttributeName: pk
KeyType: HASH
- AttributeName: sk
KeyType: RANGE
```
> Full templates including API Gateway, Cognito, IAM roles, and CloudWatch logging are generated by `serverless_stack.py` and also available in `references/architecture_patterns.md`.
**Example CDK TypeScript snippet (three-tier pattern):**
```typescript
import * as ecs from 'aws-cdk-lib/aws-ecs';
import * as ec2 from 'aws-cdk-lib/aws-ec2';
import * as rds from 'aws-cdk-lib/aws-rds';
const vpc = new ec2.Vpc(this, 'AppVpc', { maxAzs: 2 });
const cluster = new ecs.Cluster(this, 'AppCluster', { vpc });
const db = new rds.ServerlessCluster(this, 'AppDb', {
engine: rds.DatabaseClusterEngine.auroraPostgres({
version: rds.AuroraPostgresEngineVersion.VER_15_2,
}),
vpc,
scaling: { minCapacity: 0.5, maxCapacity: 4 },
});
```
### Step 4: Review Costs
Analyze estimated costs and optimization opportunities:
```bash
python scripts/cost_optimizer.py --resources current_setup.json --monthly-spend 2000
```
**Example output:**
```json
{
"current_monthly_usd": 2000,
"recommendations": [
{ "action": "Right-size RDS db.r5.2xlarge → db.r5.large", "savings_usd": 420, "priority": "high" },
{ "action": "Purchase 1-yr Compute Savings Plan at 40% utilization", "savings_usd": 310, "priority": "high" },
{ "action": "Move S3 objects >90 days to Glacier Instant Retrieval", "savings_usd": 85, "priority": "medium" }
],
"total_potential_savings_usd": 815
}
```
Output includes:
- Monthly cost breakdown by service
- Right-sizing recommendations
- Savings Plans opportunities
- Potential monthly savings
### Step 5: Deploy
Deploy the generated infrastructure:
```bash
# CloudFormation
aws cloudformation create-stack \
--stack-name my-app-stack \
--template-body file://template.yaml \
--capabilities CAPABILITY_IAM
# CDK
cdk deploy
# Terraform
terraform init && terraform apply
```
### Step 6: Validate and Handle Failures
Verify deployment and set up monitoring:
```bash
# Check stack status
aws cloudformation describe-stacks --stack-name my-app-stack
# Set up CloudWatch alarms
aws cloudwatch put-metric-alarm --alarm-name high-errors ...
```
**If stack creation fails:**
1. Check the failure reason:
```bash
aws cloudformation describe-stack-events \
--stack-name my-app-stack \
--query 'StackEvents[?ResourceStatus==`CREATE_FAILED`]'
```
2. Review CloudWatch Logs for Lambda or ECS errors.
3. Fix the template or resource configuration.
4. Delete the failed stack before retrying:
```bash
aws cloudformation delete-stack --stack-name my-app-stack
# Wait for deletion
aws cloudformation wait stack-delete-complete --stack-name my-app-stack
# Redeploy
aws cloudformation create-stack ...
```
**Common failure causes:**
- IAM permission errors → verify `--capabilities CAPABILITY_IAM` and role trust policies
- Resource limit exceeded → request quota increase via Service Quotas console
- Invalid template syntax → run `aws cloudformation validate-template --template-body file://template.yaml` before deploying
---
## Tools
### architecture_designer.py
Generates architecture patterns based on requirements.
```bash
python scripts/architecture_designer.py --input requirements.json --output design.json
```
**Input:** JSON with app type, scale, budget, compliance needs
**Output:** Recommended pattern, service stack, cost estimate, pros/cons
### serverless_stack.py
Creates serverless CloudFormation templates.
```bash
python scripts/serverless_stack.py --app-name my-app --region us-east-1
```
**Output:** Production-ready CloudFormation YAML with:
- API Gateway + Lambda
- DynamoDB table
- Cognito user pool
- IAM roles with least privilege
- CloudWatch logging
### cost_optimizer.py
Analyzes costs and recommends optimizations.
```bash
python scripts/cost_optimizer.py --resources inventory.json --monthly-spend 5000
```
**Output:** Recommendations for:
- Idle resource removal
- Instance right-sizing
- Reserved capacity purchases
- Storage tier transitions
- NAT Gateway alternatives
---
## Quick Start
### MVP Architecture (< $100/month)
```
Ask: "Design a serverless MVP backend for a mobile app with 1000 users"
Result:
- Lambda + API Gateway for API
- DynamoDB pay-per-request for data
- Cognito for authentication
- S3 + CloudFront for static assets
- Estimated: $20-50/month
```
### Scaling Architecture ($500-2000/month)
```
Ask: "Design a scalable architecture for a SaaS platform with 50k users"
Result:
- ECS Fargate for containerized API
- Aurora Serverless for relational data
- ElastiCache for session caching
- CloudFront for CDN
- CodePipeline for CI/CD
- Multi-AZ deployment
```
### Cost Optimization
```
Ask: "Optimize my AWS setup to reduce costs by 30%. Current spend: $3000/month"
Provide: Current resource inventory (EC2, RDS, S3, etc.)
Result:
- Idle resource identification
- Right-sizing recommendations
- Savings Plans analysis
- Storage lifecycle policies
- Target savings: $900/month
```
### IaC Generation
```
Ask: "Generate CloudFormation for a three-tier web app with auto-scaling"
Result:
- VPC with public/private subnets
- ALB with HTTPS
- ECS Fargate with auto-scaling
- Aurora with read replicas
- Security groups and IAM roles
```
---
## Input Requirements
Provide these details for architecture design:
| Requirement | Description | Example |
|-------------|-------------|---------|
| Application type | What you're building | SaaS platform, mobile backend |
| Expected scale | Users, requests/sec | 10k users, 100 RPS |
| Budget | Monthly AWS limit | $500/month max |
| Team context | Size, AWS experience | 3 devs, intermediate |
| Compliance | Regulatory needs | HIPAA, GDPR, SOC 2 |
| Availability | Uptime requirements | 99.9% SLA, 1hr RPO |
**JSON Format:**
```json
{
"application_type": "saas_platform",
"expected_users": 10000,
"requests_per_second": 100,
"budget_monthly_usd": 500,
"team_size": 3,
"aws_experience": "intermediate",
"compliance": ["SOC2"],
"availability_sla": "99.9%"
}
```
---
## Output Formats
### Architecture Design
- Pattern recommendation with rationale
- Service stack diagram (ASCII)
- Monthly cost estimate and trade-offs
### IaC Templates
- **CloudFormation YAML**: Production-ready SAM/CFN templates
- **CDK TypeScript**: Type-safe infrastructure code
- **Terraform HCL**: Multi-cloud compatible configs
### Cost Analysis
- Current spend breakdown with optimization recommendations
- Priority action list (high/medium/low) and implementation checklist
---
## Reference Documentation
| Document | Contents |
|----------|----------|
| `references/architecture_patterns.md` | 6 patterns: serverless, microservices, three-tier, data processing, GraphQL, multi-region |
| `references/service_selection.md` | Decision matrices for compute, database, storage, messaging |
| `references/best_practices.md` | Serverless design, cost optimization, security hardening, scalability |
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